MCPcopy Create free account

hub / github.com/beabevi/ESAN / functions

Functions105 in github.com/beabevi/ESAN

⨍ Functions 105◇ Types & classes 26
↓ 7 callersFunctionpolicy2transform
(policy: str, num_hops, process_subgraphs=lambda x: x, pbar=None)
data.py:525
↓ 5 callersMethod__init__
(self, num_tasks, num_layer=5, in_dim=300, emb_dim=300, gnn_type='gin', num_random_features=0
models.py:23
↓ 5 callersFunctionpreprocess
(dataset, transform)
data.py:163
↓ 4 callersMethod__init__
emb_dim (int): node embedding dimensionality
conv.py:16
↓ 4 callersMethodseparate_data
(self, seed, fold_idx)
data.py:78
↓ 3 callersMethod__init__
(self, fraction)
data.py:95
↓ 3 callersFunctioneval
(model, device, loader, evaluator, voting_times=1)
main.py:41
↓ 2 callersMethodeval
(self, input_dict)
utils.py:201
↓ 2 callersFunctionsubgraph_pool
(h_node, batched_data, pool)
models.py:9
↓ 2 callersFunctionto_undirected
r"""Converts the graph given by :attr:`edge_index` to an undirected graph such that :math:`(j,i) \in \mathcal{E}` for every edge :math:`(i,j) \in
data.py:123
↓ 1 callersFunctionS2V_to_PyG
(data)
data.py:334
↓ 1 callersMethodacc
(self, input_dict)
utils.py:154
↓ 1 callersFunctionget_data
(args, fold_idx)
utils.py:18
↓ 1 callersFunctionget_model
(args, in_dim, out_dim, device)
utils.py:102
↓ 1 callersFunctionload_data
dataset: name of dataset test_proportion: ratio of test train split seed: random seed for random splitting of dataset
data.py:344
↓ 1 callersMethodmae
(self, input_dict)
utils.py:169
↓ 1 callersFunctionmain
()
data.py:540
↓ 1 callersFunctionmain
()
main.py:164
↓ 1 callersMethodprocess_CSL
(self)
csl_data.py:90
↓ 1 callersFunctionreset_wandb_env
()
main.py:69
↓ 1 callersFunctionrun
(args, device, fold_idx, sweep_run_name, sweep_id, results_queue)
main.py:80
↓ 1 callersMethodto_subgraphs
(self, data)
data.py:213
↓ 1 callersFunctiontrain
(model, device, loader, optimizer, criterion, epoch, fold_idx)
main.py:19
↓ 1 callersFunctionunbatch_subgraphs
(data)
data.py:164
Method__call__
(self, data)
data.py:98
Method__call__
(self, data)
data.py:197
Method__inc__
(self, key, value)
data.py:115
Method__init__
(self, task_type)
utils.py:151
Method__init__
(self, num_tasks)
utils.py:183
Method__init__
(self, num_tasks, num_layer=5, in_dim=300, emb_dim=300, gnn_type='gin', num_random_features=0
models.py:66
Method__init__
(self, subgraph_gnn, channels, num_tasks, invariant)
models.py:94
Method__init__
(self, num_layers, in_dim, emb_dim, num_tasks, feature_encoder, GNNConv)
models.py:149
Method__init__
(self, encoder)
models.py:210
Method__init__
(self, policy, emb_dim)
models.py:220
Method__init__
(self, root: str, name: str, split: str = "train", transform: Optional[Callable] = None,
csl_data.py:22
Method__init__
(self, root: str, name: str, transform=None, pre_transform=None,
data.py:38
Method__init__
(self, process_subgraphs=lambda x: x, pbar=None)
data.py:193
Method__init__
(self, num_hops, add_node_idx=False, process_subgraphs=lambda x: x, pbar=None)
data.py:279
Method__init__
g: a networkx graph label: an integer graph label node_tags: a list of integer node tags node_feature
data.py:315
Method__init__
( self, root, name, transform=None, pre_transform=
data.py:440
Method__init__
(self, in_dim, emb_dim)
conv.py:43
Method__init__
(self, in_dim, emb_dim)
conv.py:66
Method__init__
(self, in_dim, emb_dim)
conv.py:82
Method__init__
emb_dim (int): node embedding dimensionality num_layer (int): number of GNN message passing layers
conv.py:118
Method__init__
(self, root, name=None, transform=None, pre_transform=None, pre_filter=None)
gnn_rni_data.py:15
Method__repr__
(self)
csl_data.py:136
Methoddownload
(self)
csl_data.py:76
Methoddownload
(self)
data.py:60
Methoddownload
(self)
data.py:483
Methoddownload
(self)
gnn_rni_data.py:33
Methodeval
(self, input_dict)
utils.py:177
Methodeval
(self, input_dict)
utils.py:186
Methodeval_metric
(self)
csl_data.py:116
Methodeval_metric
(self)
data.py:53
Methodeval_metric
(self)
data.py:468
Methodeval_metric
(self)
gnn_rni_data.py:62
Methodfilter
(self, record)
data.py:30
Methodforward
(self, batched_data)
models.py:59
Methodforward
(self, batched_data)
models.py:86
Methodforward
(self, batched_data)
models.py:120
Methodforward
(self, batched_data)
models.py:179
Methodforward
(self, x)
models.py:215
Methodforward
(self, x)
models.py:226
Methodforward
(self, x, edge_index, edge_attr)
conv.py:29
Methodforward
(self, x, edge_index, edge_attr)
conv.py:52
Methodforward
(self, x, edge_index, edge_attr)
conv.py:76
Methodforward
(self, x, edge_index, edge_attr)
conv.py:89
Methodforward
(self, batched_data)
conv.py:169
Methodmessage
(self, x_j, edge_attr)
conv.py:35
Methodmessage
(self, x_j, edge_attr)
conv.py:58
Methodmessage
(self, x_j, edge_attr, norm)
conv.py:104
Methodnum_node_labels
(self)
data.py:68
Methodnum_tasks
(self)
csl_data.py:112
Methodnum_tasks
(self)
data.py:49
Methodnum_tasks
(self)
data.py:464
Methodnum_tasks
(self)
gnn_rni_data.py:58
Methodprocess
(self)
csl_data.py:83
Methodprocess
(self)
data.py:63
Methodprocess
(self)
data.py:495
Methodprocess
(self)
gnn_rni_data.py:36
Methodprocessed_dir
(self)
csl_data.py:55
Methodprocessed_dir
(self)
data.py:459
Methodprocessed_dir
(self)
gnn_rni_data.py:25
Methodprocessed_file_names
(self)
csl_data.py:70
Methodprocessed_file_names
(self)
data.py:480
Methodprocessed_file_names
(self)
gnn_rni_data.py:30
Methodraw_dir
(self)
csl_data.py:51
Methodraw_dir
(self)
data.py:454
Methodraw_file_names
(self)
csl_data.py:59
Methodraw_file_names
(self)
data.py:476
Methodraw_file_names
(self)
gnn_rni_data.py:21
Methodseparate_data
(self, seed, fold_idx)
csl_data.py:123
Methodseparate_data
(self, seed, fold_idx)
data.py:509
Methodseparate_data
(self, seed, fold_idx)
gnn_rni_data.py:69
Methodtask_type
(self)
csl_data.py:120
Methodtask_type
(self)
data.py:57
Methodtask_type
(self)
data.py:472
Methodtask_type
(self)
gnn_rni_data.py:66
Methodto_subgraphs
(self, data)
data.py:218
Methodto_subgraphs
(self, data)
data.py:259
next →1–100 of 105, ranked by callers